1. Technical Field
The present invention relates to the refinement of process models and, in particular, to changing the density of a causal graph.
2. Description of the Related Art
An execution trace describes events occurring in an instance of some process. These events include tasks that are executed in the process, as well as data values input or output by the tasks. Process mining involves mining a graph of causal behavior from process execution logs and produces a process model as output. A process model may be represented by a causal graph of nodes and edges, where nodes are tasks in a process and edges represent the causality between the tasks. The model may also have gateways that show execution semantics along the edges and nodes of the graphs, such as parallelism or exclusive flows.
Process models can be mined from a set of execution traces. A mined process model could be very complex, with many nodes and edges and display spaghetti-like behavior where rarely-used or redundant paths clutter the graph. In one example, a process model could represent a pathway, such as a treatment pathway. One way to accomplish this is to find a set of execution traces that lead to a particular outcome and then mining a process model from these traces.